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DBMS > HBase vs. LMDB vs. Spark SQL vs. STSdb

System Properties Comparison HBase vs. LMDB vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameHBase  Xexclude from comparisonLMDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionWide-column store based on Apache Hadoop and on concepts of BigTableA high performant, light-weight, embedded key-value database librarySpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelWide column storeKey-value storeRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score31.60
Rank#26  Overall
#2  Wide column stores
Score2.62
Rank#117  Overall
#21  Key-value stores
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score0.13
Rank#344  Overall
#51  Key-value stores
Websitehbase.apache.orgwww.symas.com/­symas-embedded-database-lmdbspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationhbase.apache.org/­book.htmlwww.lmdb.tech/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetSymasApache Software FoundationSTS Soft SC
Initial release2008201120142011
Current release2.3.4, January 20210.9.32, January 20243.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache version 2Open SourceOpen Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCScalaC#
Server operating systemsLinux
Unix
Windows infousing Cygwin
Linux
Unix
Windows
Linux
OS X
Windows
Windows
Data schemeschema-free, schema definition possibleschema-freeyesyes
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesyes infoprimitive types and user defined types (classes)
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesnononono
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsno
APIs and other access methodsJava API
RESTful HTTP API
Thrift
JDBC
ODBC
.NET Client API
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresyes infoCoprocessors in Javanonono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
nonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)ACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnonono

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More resources
HBaseLMDBSpark SQLSTSdb
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